The proportion of people with COVID infections that were missed by Innova lateral flow tests (LFT) is substantial enough to be of clinical importance, particularly for the asymptomatic, warn experts in The BMJ.
An analysis by Professor Jonathan Deeks, PhD, and colleagues predicts that Innova would miss 20% of viral culture positive cases attending an NHS Test-and-Trace center, 29% without symptoms attending mass testing, and 81% attending university screen testing without symptoms—many more than predicted by mathematical models on which policy decisions are based.
The authors acknowledge that lateral flow tests are an important tool in controlling the pandemic but note claims that they can identify “the vast majority who are infectious” have been overstated, with risk of false reassurance to those seeking to rule-out infection.
Lateral flow tests for SARS-CoV-2 have been recommended for widespread use, largely based on predictions made by mathematical models.
While empirical data show lateral flow tests give a positive result when virus is present on a swab in high quantities—and can detect people who are likely to be infectious—the proportion missed who are infectious has not been evaluated.
To address this evidence gap, Deeks and colleagues drew on empirical data from several sources to predict the proportion of Innova lateral flow tests that produce negative results in those with a high risk of SARS-CoV-2 infectiousness. They then compared these with predictions made by influential mathematical models.
Their focus was to identify the joint probability that people are likely to be infectious (in that they have a viral culture positive result or are a secondary case) and that they test negative on Innova.
Their results are based on testing in three settings: symptomatic testing at an NHS Test-and-Trace centre, mass testing in Liverpool in residents without symptoms, and in students at the University of Birmingham.
The analysis predicted that of those with a viral culture positive result, Innova would miss 20% attending an NHS Test-and-Trace center, 29% without symptoms attending municipal mass testing, and 81% attending university screen testing without symptoms, along with 38%, 47%, and 90% of sources of secondary cases.
In comparison, two mathematical models underestimated the numbers of missed infectious individuals.
The authors stress there is the potential for error in their estimates. However, they point out that these data “are currently the best available and clearly show that missing people with current infection or who are infectious is possible in all settings.”
They argue that key models have failed to appropriately use empirical evidence to inform assumptions of test accuracy and chances of infectiousness, resulting in unrealistic overestimates of test performance, and say until new generation lateral flow tests are available that meet the regulatory performance requirements, negative test results from LFTs cannot be relied on to exclude current infection.
The study authors also point out that observational studies attempting to assess the impact on transmission as a result of testing asymptomatic non-contacts have struggled to show an effect and none seem to have examined the costs of the programs.
Meanwhile, the World Health Organization cautions against mass asymptomatic testing because of high costs, lack of evidence on the impact, and risk of diverting resources from more important activities.
